Dynamic prediction method for short-term bus passenger flow based on the Prophet model

Baoyun Sun; Zimin Wang; Yaping Yang; Honglin Lu

doi:10.1117/12.3030466

16 May 2024 Dynamic prediction method for short-term bus passenger flow based on the Prophet model

Baoyun Sun, Zimin Wang, Yaping Yang, Honglin Lu

Proceedings Volume 13160, Fourth International Conference on Smart City Engineering and Public Transportation (SCEPT 2024); 131600X (2024) https://doi.org/10.1117/12.3030466
Event: 4th International Conference on Smart City Engineering and Public Transportation (SCEPT 2024), 2024, Beijin, China

Abstract

This research employs the Prophet model, a time series forecasting tool, to tackle the intricacies and fluctuations in bus passenger flow. Through the utilization of historical ridership data, a Prophet model was formulated, accounting for seasonal changes and potential holiday impacts. Empirical results demonstrate the remarkable performance of the Prophet model in predicting bus passenger flow, showcasing high preciseness and robustness. The model not only captures cyclic ridership variations but also adjusts to seasonal dynamics and the influence of special events. In-depth analysis uncovers the model's predictive capabilities across various time scales, furnishing robust decision support for bus operators. The significance of this research is underscored by its introduction of the Prophet model into the of bus passenger flow prediction, presenting a novel and efficient tool for the analysis and prediction of short-term urban transit passenger flow. This has the potential to elevate the sustainability and service standards of public transit systems.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Baoyun Sun, Zimin Wang, Yaping Yang, and Honglin Lu "Dynamic prediction method for short-term bus passenger flow based on the Prophet model", Proc. SPIE 13160, Fourth International Conference on Smart City Engineering and Public Transportation (SCEPT 2024), 131600X (16 May 2024); https://doi.org/10.1117/12.3030466

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